{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 绘制散点图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 绘制散点图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "dataSet = np.array([[1,1],   # 必须是np.array类型，普通的数组类型不可以\n",
    "          [2,2],\n",
    "          [3,3],\n",
    "          [4,4]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 方法一\n",
    "plt.scatter(dataSet[:,0], dataSet[:,1])   # 参数为坐标\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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5wDwuAC7ubL8Y+D/gX9bamgw4j7WyJgFe1NkeAx4ALu2q+Q/gls72dcD3R933Wc7jeuDmUfc64Hz+C/ifXv8NrdR6rPoz9Kq6H3jyDCVXA7fXop8DE0kuOD/dDW6AeawJVfVYVT3U2f4TcJjTvxR81a/JgPNYEzr/Pz/deTrWeXTf7XA1cFtn+w7gzUl6fR/wyAw4jzUhyUbg7cDXlyhZkfVY9YE+gCng0VOeH2WN/sUE3tj5cfPuJK8edTP9dH5M3MrimdSp1tSanGEesEbWpPPj/UHgceCeqlpyTarqBHAceOn57bK/AeYB8I7Opbw7kmzqsX81+CLwCeBvS+xfkfVoIdB7vautxXf1h1j8NxpeB3wF2Dvifs4oyYuAHwIfq6qnunf3+COrck36zGPNrElVnayq17P4Je2XJHlNV8maWJMB5vEjYHNVvRb4Mf84y101klwJPF5VD56prMfYOa9HC4F+FDj1XXojcGxEvZy1qnrq2R83q+ouYCzJhhG31VOSMRZD8DtVtadHyZpYk37zWEtr8qyqmgfuA67o2vX3NUmyHngJq/gS4FLzqKonquqvnadfA95wnlsbxGXAVUl+B3wPeFOSb3fVrMh6tBDo+4D3du6suBQ4XlWPjbqp5UrysmevoSW5hMW1eWK0XZ2u0+OtwOGq+vwSZat+TQaZxxpak8kkE53tceAtwG+7yvYB7+tsXwvcW53fyK0Wg8yj63cxV7H4u49Vpap2VtXGqtrM4i88762qd3eVrch69P2S6FFL8l0W7zbYkOQo8CkWf1lCVd0C3MXiXRWPAH8G3j+aTs9sgHlcC3woyQlgAbhutf2F67gMeA9wqHOtE+CTwMthTa3JIPNYK2tyAXBbknUsvun8oKruTPIZYKaq9rH45vWtJI+weCZ43ejaXdIg8/hIkquAEyzO4/qRdbtM52M9/Oi/JDWihUsukiQMdElqhoEuSY0w0CWpEQa6JDXCQJekRhjoktSI/weLr/H6UozklwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 方法二\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)   # If no positional arguments are passed, defaults to (1, 1, 1)或(111)\n",
    "ax.scatter(dataSet[:,0], dataSet[:,1])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 绘制不同大小的散点图，以方法一为例，方法二类似"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 参数1，2是坐标，参数3是大小。大小乘以15是为了让效果更明显\n",
    "plt.scatter(dataSet[:,0], dataSet[:,1], s=15*np.array(dataSet[:,0]))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 绘制不同颜色的散点图，以方法一为例，方法二类似"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 参数1，2是坐标，参数3是颜色，此时必须标明\"c=\"\n",
    "# plt.scatter(x,y,c)\n",
    "# 参数1，2是坐标，参数3是大小，参数4是颜色，此时不需要标明参数名\n",
    "# plt.scatter(x,y,s,c)\n",
    "\n",
    "# 颜色*15是为了让效果更明显\n",
    "plt.scatter(dataSet[:,0], dataSet[:,1], c=15*np.array(dataSet[:,0]))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 绘制圆环"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<function matplotlib.pyplot.show(*args, **kw)>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "# 0,0代表坐标\n",
    "# s=150是大小\n",
    "# c代表填充颜色，如果c='none'表示无填充\n",
    "# edgecolor代表边框颜色，默认没有颜色。\n",
    "# 无填充颜色+有边框颜色就是圆环的效果\n",
    "# linewidth代表边框的粗细程度\n",
    "plt.scatter(0,0, s=150, c='none', alpha=0.7, linewidth=1.5, edgecolor='#AB3319')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 不同的形状"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "# 0,0代表坐标\n",
    "# s=150是大小\n",
    "# c代表填充颜色，如果c='none'表示无填充\n",
    "# edgecolor代表边框颜色，默认没有颜色。\n",
    "# 无填充颜色+有边框颜色就是圆环的效果\n",
    "# linewidth代表边框的粗细程度\n",
    "plt.scatter(0,0, s=150, marker='+')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
